62 articles tagged with “gpu”.
Nvidia's RTX Spark N1X, an Arm-based laptop SoC with RTX Blackwell graphics and large unified memory for running local AI models, ships in Windows laptops from six manufacturers.
NVIDIA is launching RTX Spark, a Windows PC aimed at creators, gamers and AI agents, with partner launch events held worldwide.
NVIDIA has added DLSS 4.5 controls to its GeForce NOW cloud gaming service, letting members adjust how supported games look and perform without upgrading hardware.
NVIDIA introduces RTX Spark, a superchip-based PC platform offering up to 128GB of unified memory and 1 petaflop of AI compute, with a ready global PC app ecosystem.
AWS describes how to run multi-node LLM inference on Amazon EKS using pre-built Ray LLM Deep Learning Containers, splitting prefill and decode across two GPU nodes behind one OpenAI-compatible endpoint.
At the Open Compute Project Global Summit, NVIDIA announced new partnerships and contributions and opened its Vera Rubin architecture to support scaling AI infrastructure.
Microsoft announced Maia 300, its third-generation in-house AI chip built as its primary AI inference system, with production rollout slated for 2027.
AWS outlines a reference architecture for sharing a single SageMaker HyperPod EKS cluster across teams, combining IAM Identity Center authentication, per-team isolation, task governance, and namespace-level chargeback.
Microsoft disclosed the specs and price of its Surface Laptop Ultra, AI PCs running on Nvidia chips and designed to run AI models and agents.
Microsoft's Surface RTX Spark Dev Box is up for preorder at roughly $6,000, shipping in November, powered by Nvidia's Arm-based RTX Spark platform with 128GB of unified memory.
GPT-6 Astra Ultrafast, running on NVIDIA Blackwell GPUs, is now available in the OpenAI API and to eligible ChatGPT Work and Codex users, with up to 8x faster token generation than Astra Standard.
Google sent its first advanced chip into orbit as an early step toward space data centers, which could require roughly 1,800 SpaceX Starship launches.
AWS details deploying a three-agent music production pipeline on Amazon Bedrock AgentCore Runtime Instances, with agents sharing a GPU instance and filesystem to produce a finished track.
AWS presents an architecture combining Amazon EKS, EFA, and S3 to scale Mixture-of-Experts reinforcement learning, reporting a 40% increase in aggregate rollout throughput for RLHF and GRPO training.
AWS explains how to deploy the WhisperX Deep Learning Container on Amazon SageMaker AI real-time and asynchronous endpoints for word-level, speaker-labeled transcription.
The article discusses the use of NVIDIA Warp and MjWarp to enhance robotics simulation and improve learning workflows, providing insights into their capabilities.
NVIDIA has released Isaac ROS 5.0, a set of GPU-accelerated packages built on the ROS open framework to support robotics applications that perceive, reason, and act.
NVIDIA has launched DSX Ready, a program to qualify power and cooling products designed to fit AI factory computing architectures amid growing infrastructure constraints.
AWS introduced SageMaker HyperPod Inference Gateway, a Kubernetes-native, GPU-aware routing add-on for Amazon EKS that routes inference requests using real-time GPU signals.
Huawei is accelerating the launch of its Ascend 960DT AI chip, targeting a Q1 2027 release as it seeks to compete with Nvidia and close China's AI computing gap with the U.S.
A technical guide to using NVIDIA's Resiliency Extension with PyTorch FSDP on Amazon EKS, covering async checkpointing and fast GPU fault recovery with H100 benchmarks.
NVIDIA's Ian Buck spoke on AI factory energy efficiency at the AI Infra Summit, showcasing Vera Rubin and DSX platform advancements centered on tokens per watt.
Perplexity's Portable Computer, a local version of its Computer agent, is now available on Windows and accelerated by NVIDIA RTX, running local models to plan and execute multistep tasks on-device.
Nvidia's Jensen Huang outlines why he expects the company to grow 70% next year and pushes back on claims that its deals are circular.
d-Matrix announced it will adopt NVIDIA NVLink Fusion to link its next-generation Raptor XPUs to NVIDIA's scale-up and scale-out networking and MGX rack architecture.
Nvidia announced Personal AI Router (PAIR), free open-source software that discovers and connects compatible PCs on a network to run local AI inference and agentic workflows.
Nvidia is launching its DLSS 5 AI upscaling technology this week for RTX 50-series GPUs and GeForce Now, with NBA 2K27 as the only supported game at release.
Nvidia has invested $3.5 billion in MediaTek, a move seen as part of its plan to stay essential to AI infrastructure as Big Tech companies develop their own AI chips.
New data center systems reportedly gain efficiency through smarter traffic control rather than relying solely on more processor cycles, extending Nvidia's advantage beyond the GPU.
Lambda secured $1B in private debt to buy Nvidia AI chips and lease them to Microsoft, adding to a series of loans that reflect the high cost of the AI boom.
Amazon plans to add another 2 million Nvidia GPU chips to its data centers over the next two years, citing surging demand and an expanded partnership with Nvidia.
Nvidia is projecting $100 billion in quarterly revenue, a milestone previously reached by Amazon, Apple, and Alphabet, driven by record data center sales.
NVIDIA expands its NVLink Fusion platform with NVHBM custom high-bandwidth memory, targeting the infrastructure demands of AI agents and trillion-parameter workloads.
OpenAI says its Jalapeño chip, an ASIC built with Broadcom for AI inference, delivers lower latency and higher throughput than rival systems.
NVIDIA describes AI factories as full-scale infrastructure whose value is measured by delivered output metrics, and considers how custom XPUs fit into that model.
NVIDIA announced an extension of its Vera Rubin NVL72 rack-scale system aimed at faster token generation for agentic AI systems, stressing coordination across all layers of the AI factory.
Nvidia has partnered with data center developer Cloverleaf, extending its ongoing investment in data center development.
As spending on data centers and GPUs surges, a startup is tackling the lack of a standard way to price AI compute or hedge against price changes.
VentureBeat has appointed Rob Strechay, formerly of theCUBE Research, as its first Lead Analyst and founding analyst of VentureBeat Research, deepening its enterprise AI coverage.
Nvidia and firms including Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR are assembling $500 billion in financing to frame compute as a new asset class, a claim The Verge scrutinizes.
A Hugging Face Blog post describes achieving 33 percentage points more utilization on the same cluster by changing the order rather than the hardware.
NVIDIA frames AI factories as the defining infrastructure of the AI era, requiring advanced chips, packaging, memory, networking, plus land and power.
An AWS blog post details building a tiered KV cache on Amazon SageMaker HyperPod with Curvine, extending the cache into a shared NVMe pool so replicas reuse cache on cost-efficient instances.
NVIDIA announced partnerships with six major financial firms to create independent financing platforms aimed at mobilizing over $500 billion in third-party capital for AI infrastructure buildout.
NVIDIA outlines why scaling AI compute requires rethinking power delivery, noting that the challenge lies in how electricity moves from the grid to the GPU, not just total wattage.
Firebird, an emerging AI cloud, has launched what it describes as the CIS region's largest AI factory in Armenia, using NVIDIA accelerated computing and Dell high-performance infrastructure.
AMD reported that AI-driven demand more than doubled its data center revenue to $5.8 billion, while gaming hardware sales slowed due to price hikes and component shortages.
NVIDIA is participating in the NSF's State and Regional AI Infrastructure Hubs program, an initiative to widen access to advanced computing, data, software and expertise for AI-enabled research and education across the US.
A Hugging Face Blog post addresses GPU management, framing idle GPUs as a costly problem akin to grounded aircraft.
MIT Technology Review reports that engineers at Samsung's semiconductor division are increasingly applying to work for its South Korean rival SK Hynix.
NVIDIA is working with Cadence and Synopsys to optimize electronic design automation applications for its Vera CPU, which it is deploying to accelerate chip design.
South Korea's president and top business and research leaders met with NVIDIA and ecosystem partners at an AI Summit in San Francisco to advance the country's AI development.
AMD introduced Helios, a rack-scale AI system that the company says will begin shipping to customers later this year, in a challenge to rival Nvidia.
Wistron opened its first U.S. manufacturing plant in Fort Worth, Texas — a 324,000-square-foot greenfield facility producing superchips used in NVIDIA AI systems.
NVIDIA's Vera Rubin is moving into production, with NVL72 racks deployed at major cloud partners and backed by a supply chain spanning over 350 factory sites in 30 countries.
NVIDIA has announced Spectrum-6, a networking milestone built for Vera Rubin and aimed at gigascale AI factories connecting hundreds of thousands of GPUs and CPUs.
Bristol Myers Squibb announced it will deploy a second NVIDIA DGX SuperPOD, built on NVIDIA Vera Rubin, to expand one of the largest AI clusters in life sciences.
NVIDIA's Vera Rubin is positioned to reduce cost per token for post-training workloads through codesign, maximizing intelligence per dollar for agentic AI.
A $400 million chip-backed loan highlights a move by early GPU financiers toward inference chips as part of the next wave of AI infrastructure financing.
NVIDIA frames performance per watt as the defining efficiency metric for AI infrastructure, arguing power is the main constraint on how many tokens an AI factory can generate.
Every word an LLM generates has a cost in compute, memory, and time. Here is what actually happens during inference — and why it explains latency, throughput, and per-token pricing.
Modern AI runs on a scarce resource: specialized compute. This feature unpacks why GPUs became the bottleneck, why everyone is building custom chips, and what it means for the balance of power in AI.